A Hybrid Trajectory Planning Strategy for Intelligent Vehicles in On-Road Dynamic Scenarios
Efficient trajectory planning for intelligent vehicles in dynamic environments is a non-trivial task due to the diversity and complexity of driving scenarios. It requires the planner to be capable of responding to the changes in driving scenarios in real-time. This paper proposes a hybrid trajectory planning framework by combining the sampling- and numerical optimization-based approaches to cope with the complex driving scenarios. First, a risk field model is introduced to assess the risks with the static and moving obstacles. Then, the sampling-based approach is used to generate collision-free trajectory candidates via the Path Velocity Decomposition method. Thus, the optimal behavior trajectory can be obtained by considering curve smoothness, collision risk, and travel time. The optimization-based method is adopted to optimize the behavior trajectory to guarantee safety, vehicle dynamics stability, and driving comfort using the Sequential Quadratic Programming within the spatio-temporal boundaries. Finally, the proposed framework is examined in typical dynamic driving scenarios through simulation, and the results verify its competency in generating high-quality trajectories in real-time.
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Availability:
- Find a library where document is available. Order URL: http://worldcat.org/issn/00189545
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Supplemental Notes:
- Copyright © 2023, IEEE.
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Authors:
- Wang, Mingqiang
- Zhang, Lei
- Zhang, Zhiqiang
- Wang, Zhenpo
- Publication Date: 2023-3
Language
- English
Media Info
- Media Type: Web
- Features: References;
- Pagination: pp 2832-2847
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Serial:
- IEEE Transactions on Vehicular Technology
- Volume: 72
- Issue Number: 3
- Publisher: Institute of Electrical and Electronics Engineers (IEEE)
- ISSN: 0018-9545
- Serial URL: http://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=25
Subject/Index Terms
- TRT Terms: Intelligent vehicles; Optimization; Risk assessment; Trajectory control; Vehicle trajectories
- Subject Areas: Highways; Vehicles and Equipment;
Filing Info
- Accession Number: 01878246
- Record Type: Publication
- Files: TRIS
- Created Date: Apr 3 2023 9:52AM